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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana TELKOMNIKA (Telecommunication Computing Electronics and Control) JOIN (Jurnal Online Informatika) Jurnal Ilmiah Universitas Batanghari Jambi JISTech (Journal of Islamic Science and Technology) Building of Informatics, Technology and Science Majalah Ilmiah Warta Dharmawangsa Reswara: Jurnal Pengabdian Kepada Masyarakat Syntax: Journal of Software Engineering, Computer Science and Information Technology Djtechno: Jurnal Teknologi Informasi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY JURNAL PUBLIK REFORM Jurnal Pengabdian Masyarakat CompTech : Jurnal Ilmu Komputer dan Teknologi
Zulham Zulham
Universitas Dharmawangsa
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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Implementasi Sistem Informasi Pengaduan Masyarakat Berbasis Web dengan Automatic Ticketing Workflow Hendry Hendry; Supiyandi Supiyandi; Chairul Rizal; Muhammad Eka; Zulham Zulham
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.694

Abstract

Penanganan pengaduan masyarakat sering terhambat oleh proses manual yang tidak terstruktur, menyebabkan respons yang lambat dan hilangnya riwayat penanganan. Penelitian ini mengembangkan dan menerapkan Sistem Informasi Pengaduan Masyarakat berbasis web yang dilengkapi dengan mekanisme automatic ticketing workflow untuk memastikan setiap laporan tercatat, terverifikasi, dan dialirkan ke unit terkait secara otomatis. Sistem dirancang menggunakan arsitektur modular dengan fitur inti berupa pelacakan status tiket, notifikasi otomatis, serta dashboard analitik untuk memantau kinerja penanganan. Metode pengembangan yang digunakan adalah pendekatan waterfall dengan tahapan analisis kebutuhan, desain sistem, implementasi, dan pengujian. Hasil penerapan menunjukkan bahwa otomatisasi alur tiket mampu mempersingkat waktu disposisi, meningkatkan akurasi distribusi laporan, dan memberikan transparansi proses bagi pengguna maupun admin. Pengujian fungsional juga menunjukkan tingkat keberhasilan fitur sebesar lebih dari 95%, menandakan sistem berjalan stabil dan memenuhi kebutuhan operasional. Temuan ini menegaskan bahwa integrasi automatic ticketing dalam sistem pengaduan mampu meningkatkan efisiensi, akuntabilitas, serta kualitas pelayanan publik.
Pengelompokkan Jenis Surat Masuk di Dinas Komunikasi dan Informatika Menggunakan Metode K-Means Clustering Sartika Siregar; Zulham Zulham; Arif Rahman
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.935

Abstract

Effective management of incoming mail administration is a crucial factor in improving performance and service delivery in government agencies. However, manual processing of incoming mail is often inefficient due to the ever-increasing volume of data and the diverse content, which can make archiving, data retrieval, and decision-making difficult. Therefore, a method capable of automatically grouping incoming mail data is needed. One data mining technique that can be used is K-Means clustering. This study aims to group incoming mail at the Medan City Communications and Informatics Office based on content similarity. The research process involved several stages: text preprocessing, including cleaning, tokenization, stopword removal, and stemming. Then, weighting was performed using the TF-IDF method, followed by clustering with the K-Means algorithm. Data processing was performed using the Python programming language on the Google Colaboratory (Google Colab) platform. The results showed that the incoming mail data could be grouped into three clusters. The first cluster, 3.9%, contains letters related to planning and strategic document preparation; the second cluster, 85.9%, is a group of personnel administration letters, specifically regarding the appointment to functional positions; and the third cluster, 10.2%, contains letters related to operational and routine agency activities. The results of this grouping indicate that most incoming letters are dominated by personnel administration. Thus, applying the K-Means Clustering method can help systematically group incoming letters and support more effective, efficient archive management.
Co-Authors Afni Nia Sari Andy Satria Asyahri Hadi Nasyuha Batubara, Supina Budi Antoro Buyung Solihin Hasugian Chairul Rizal Chinthia, Maulidania Mediawati Cut Zahri Dicky Kurniawan Ega Evinda Putri Eka Pandu Cynthia Eka, Muhammad Eli Triaulia Elyas, Ananda Hadi Fachryan Ababil Firah, Al Fitri Wulandari Hafizah, Akhwani Shifa Harun Harun Hayuni, Sabrina Hendry Hendry Heru Pahlevi Himawan, Rizky Ibnu Rusydi Indah Pratiwi J. Prayoga, J. Prayoga Jessica Syahvira Leonardo Silalahi M Wahyu Sembaga M. Arif Rahman M. Eka Meila Nida Sadanah Mochammad Iswan Muhammad Eka Muhammad Iqbal Nadia, Isra Nasution, Mardiah Ngatno Sahputra Ngatno Sahputra Nico Dipayo Ningrum, Apriya Nofyta Andryani Okla Rahayu Putra, Randi Rian Putri, Audi Amelia Rahman, M. Arif Rahmat Sulaiman Naibaho Rikie Kartadie Rizky, Firahmi Rusydi Rusydi Sabrina Aulia Rahmah salamah salamah Samara Aflahani Sartika Siregar satrianto, hendri Sri Wahyuni Sri Wahyuni Supiyandi Supiyandi Syahputri, Nimah Yasir, Amru Zaman, Khamarul Zelvi Gustiana Zhafar, Raihan